Classification of savanna tree species, in the Greater Kruger National Park region, by integrating hyperspectral and LiDAR data in a Random Forest data mining environment

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 69, Issue , 2012, Pages 167-179

  Naidoo, L ^a   Cho, M A ^a   Mathieu, R ^a   Asner, G ^b  

^a DSI CSIR Nanotechnology Innovation Centre   (South Africa)

^b GEOPHYSICAL LABORATORY   (United States)

Author keywords

Predictor datasets; Random Forest; Savanna tree species; Spectral variability; Tree height

Indexed keywords

DATA SETS; RANDOM FORESTS; SPECTRAL VARIABILITY; TREE HEIGHT; TREE SPECIES;

CHLOROPHYLL; CLASSIFICATION (OF INFORMATION); DECISION TREES; ECOSYSTEMS; OPTICAL RADAR; PHOTOMAPPING; VEGETATION;

FORESTRY;

ACCURACY ASSESSMENT; CHLOROPHYLL; DATA MINING; DATA SET; FOOD PRODUCTION; FUELWOOD; HERBIVORY; LIDAR; MAPPING; NATIONAL PARK; NDVI; SAVANNA; VEGETATION CLASSIFICATION;

CHLOROPHYLLS; CLASSIFICATION; ECOSYSTEMS; FORESTRY; INFORMATION RETRIEVAL; PLANTS; RADAR; SPECIES IDENTIFICATION; TREES;

KRUGER NATIONAL PARK; SOUTH AFRICA;

EID: 84859644121     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2012.03.005     Document Type: Article

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